Triple

T32599341
Position Surface form Disambiguated ID Type / Status
Subject Ferdinand, Duke of Parma E833320 entity
Predicate mother P120 FINISHED
Object Louise Élisabeth of France
Louise Élisabeth of France was a French princess, eldest daughter of King Louis XV, who became Duchess of Parma through her marriage to Philip, Duke of Parma.
E2283999 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Louise Élisabeth of France | Statement: [Ferdinand, Duke of Parma, mother, Louise Élisabeth of France]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Louise Élisabeth of France
Triple: [Ferdinand, Duke of Parma, mother, Louise Élisabeth of France]
Generated description
Louise Élisabeth of France was a French princess, eldest daughter of King Louis XV, who became Duchess of Parma through her marriage to Philip, Duke of Parma.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f3492ab63c8190aec24d5003b47c29 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c698588c819088e3bc33318651f3 completed May 3, 2026, 3:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a4312f1c3108190bd462af64300255c completed June 30, 2026, 12:50 a.m.
NEDg Description generation batch_6a4314d0765c8190b2635f98877fdb5d completed June 30, 2026, 12:58 a.m.
NED2 Entity disambiguation (via description) batch_6a4315906ff8819096966a483256fc98 completed June 30, 2026, 1:02 a.m.
Created at: May 1, 2026, 1:05 a.m.